Triple

T15168254
Position Surface form Disambiguated ID Type / Status
Subject Katherine LaNasa E362415 entity
Predicate notableWork P4 FINISHED
Object Love Monkey
Love Monkey is a short-lived 2006 American television dramedy series about a music executive navigating his personal and professional life in New York City.
 E1142478 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Love Monkey | Statement: [Katherine LaNasa, notableWork, Love Monkey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Love Monkey
Context triple: [Katherine LaNasa, notableWork, Love Monkey]
  • A. Macaca
    Macaca is a diverse genus of Old World monkeys that includes numerous macaque species widely distributed across Asia and parts of North Africa.
  • B. Monkey
    Monkey is a swift, acrobatic kung fu master and member of the Furious Five in the Kung Fu Panda franchise, known for his playful personality and agility in combat.
  • C. Monkey
    "Monkey" is a song by the British rock band Bush from their 1994 debut album *Sixteen Stone*.
  • D. Steve the monkey
    Steve the monkey is a comedic, gadget-wearing lab assistant and sidekick in the animated film "Cloudy with a Chance of Meatballs."
  • E. Chee-Chee the monkey
    Chee-Chee the monkey is a loyal, talkative simian companion of Doctor Dolittle in Hugh Lofting’s classic children’s book series.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Love Monkey
Triple: [Katherine LaNasa, notableWork, Love Monkey]
Generated description
Love Monkey is a short-lived 2006 American television dramedy series about a music executive navigating his personal and professional life in New York City.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Love Monkey
Target entity description: Love Monkey is a short-lived 2006 American television dramedy series about a music executive navigating his personal and professional life in New York City.
  • A. Macaca
    Macaca is a diverse genus of Old World monkeys that includes numerous macaque species widely distributed across Asia and parts of North Africa.
  • B. Monkey
    Monkey is a swift, acrobatic kung fu master and member of the Furious Five in the Kung Fu Panda franchise, known for his playful personality and agility in combat.
  • C. Monkey
    "Monkey" is a song by the British rock band Bush from their 1994 debut album *Sixteen Stone*.
  • D. Steve the monkey
    Steve the monkey is a comedic, gadget-wearing lab assistant and sidekick in the animated film "Cloudy with a Chance of Meatballs."
  • E. Chee-Chee the monkey
    Chee-Chee the monkey is a loyal, talkative simian companion of Doctor Dolittle in Hugh Lofting’s classic children’s book series.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0064dba588190a4341775b472a6d3 completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec889c3408190bdfc75ce72dd5a62 completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec93109c08190a3499e4520e31604 completed May 9, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69fecc6fa8f88190aa6956e6e2b1f8ab completed May 9, 2026, 5:55 a.m.
Created at: April 10, 2026, 3:08 a.m.